IIT Madras Alumni Association (IITMAA) has announced the top 50 teams in its Machine Learning Hackathon Contest. The Hackathon is a part of its Annual Flagship Event 'Sangam,' which will deliver a strategy document for 'Reimagining India in 2030' to the Prime Minister's Office (PMO). IIT Madras is celebrating its Diamond Jubilee (60 years) this year and these initiatives are intended to be part of the Alumni's contribution to the nation's growth.
The scenario for the Hackathon involved an Indian Smart City's Traffic Police Department which wishes to use Machine Learning/Artificial Intelligence techniques to solve their traffic crisis. The department has also collected traffic volume patterns and climate conditions observed for over four years. The given task for the Students participating in the Hackathon was to help the police predict traffic volume for given duration and climate conditions.
As many as 3,266 teams participated in the Phase 1 online hackathon with the top teams making predictions with an accuracy of up to 99.97 per cent using Regression models such as 'XGBoost,' supported by adept Feature Engineering techniques.
The Top 50 teams of Phase I came from Institutions across the country including IIT Bombay, IIT Delhi, IIT Kharagpur, IIT Roorkee and IIT Madras besides Indian Statistical Institute, National Institute of Technology - Jamshedpur, National Institute of Technology - Patna and Army Institute of Technology - Pune.
The Demographics of participants include 257 teams from Delhi NCR, 288 teams from Mumbai and Pune; 509 teams from Chennai and Hyderabad ; 437 teams from Bengaluru, 103 teams from Kolkata, 50 teams from Coimbatore and 1,622 from other parts of the country.
In Phase 2, IITMAA will conduct a Hackathon onsite at the IIT Madras campus on 24th and 25th August 2019. The Hackathon will provide the short-listed teams Time series data on air quality and pollution recorded by IoT (Internet of Things) devices from 'Project Kaatru (Air)', a research project of Prof. Raghunathan Rengaswamy, IIT Madras and supported by Robert Bosch Centre for Data Science and Artificial Intelligence, IIT Madras.
Highlighting the importance of this Hackathon and how it can help the community at large, Mr. Krishnan Narayanan, Co-Chair, Sangam 2019 and President, itihaasa Research and Digital, said, "Such highly accurate AI / ML models and analysis can not only help Indian Traffic Governance Systems predict and thereby, effectively manage, the traffic volume for a defined time-period but also help analyze a trend to observe the correlation between Air Pollution Index and Traffic Volume."
Speaking about how IIT Madras Alumni will contribute to India's development through Sangam 2019, Mr. Sriram Viji, Chair Sangam 2019 and Deputy Managing Director Brakes India said, "Sangam will suggest some long-term solutions and directional recommendations that provide an arc of transformation for the country, while being inclusive, especially of the women and the youth in India."
At Sangam 2019, IIT Madras Alumni will be preparing a strategy document, detailing ideas 'Reimagining India in 2030 across the following five pillars:
- Asserting leadership in Business, Economy and Technology
- Nurturing a Global Innovation and Entrepreneurship Ecosystem
- Harnessing technology for Agriculture & Sustainable Living
- Leveraging Technology for All and delivering Societal Impact
- Human Enablement - Education and Skill development for the jobs in the future
The Document being presented to the PMO will also include inputs from the 'Voice of Alumni', 'Voice of Women' and 'Voice of Youth' surveys. Along with the Office of the Prime Minister of India, the document will also be submitted to other relevant Governmental and industry bodies/agencies and to the office of the Director of IIT Madras to provide inputs for the next Strategy document of the institute.
IITMAA is also targeting for 5,000 of its alumni to take the 'I4India@2030 Pledge'. The IIT Madras Alumni Association will implement some of the key recommendations from the Sangam 2019 report over the next year leading up to the next edition of Sangam.
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